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Update infer_cli.py #611

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129 changes: 71 additions & 58 deletions src/f5_tts/infer/infer_cli.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,6 +87,12 @@
default=1.0,
help="Adjust the speed of the audio generation (default: 1.0)",
)
parser.add_argument(
"--cross_fade_duration",
type=float,
default=0.15,
help="Duration of cross-fade between audio segments in seconds (default: 0.15)",
)
args = parser.parse_args()

config = tomli.load(open(args.config, "rb"))
Expand All @@ -95,7 +101,7 @@
ref_text = args.ref_text if args.ref_text != "666" else config["ref_text"]
gen_text = args.gen_text if args.gen_text else config["gen_text"]
gen_file = args.gen_file if args.gen_file else config["gen_file"]

cross_fade_duration = args.cross_fade_duration if hasattr(args, 'cross_fade_duration') else config.get('cross_fade_duration', 0.15)
# patches for pip pkg user
if "infer/examples/" in ref_audio:
ref_audio = str(files("f5_tts").joinpath(f"{ref_audio}"))
Expand Down Expand Up @@ -163,63 +169,70 @@
ema_model = load_model(model_cls, model_cfg, ckpt_file, mel_spec_type=mel_spec_type, vocab_file=vocab_file)


def main_process(ref_audio, ref_text, text_gen, model_obj, mel_spec_type, remove_silence, speed):
main_voice = {"ref_audio": ref_audio, "ref_text": ref_text}
if "voices" not in config:
voices = {"main": main_voice}
else:
voices = config["voices"]
voices["main"] = main_voice
for voice in voices:
voices[voice]["ref_audio"], voices[voice]["ref_text"] = preprocess_ref_audio_text(
voices[voice]["ref_audio"], voices[voice]["ref_text"]
)
print("Voice:", voice)
print("Ref_audio:", voices[voice]["ref_audio"])
print("Ref_text:", voices[voice]["ref_text"])

generated_audio_segments = []
reg1 = r"(?=\[\w+\])"
chunks = re.split(reg1, text_gen)
reg2 = r"\[(\w+)\]"
for text in chunks:
if not text.strip():
continue
match = re.match(reg2, text)
if match:
voice = match[1]
else:
print("No voice tag found, using main.")
voice = "main"
if voice not in voices:
print(f"Voice {voice} not found, using main.")
voice = "main"
text = re.sub(reg2, "", text)
gen_text = text.strip()
ref_audio = voices[voice]["ref_audio"]
ref_text = voices[voice]["ref_text"]
print(f"Voice: {voice}")
audio, final_sample_rate, spectragram = infer_process(
ref_audio, ref_text, gen_text, model_obj, vocoder, mel_spec_type=mel_spec_type, speed=speed
)
generated_audio_segments.append(audio)

if generated_audio_segments:
final_wave = np.concatenate(generated_audio_segments)

if not os.path.exists(output_dir):
os.makedirs(output_dir)

with open(wave_path, "wb") as f:
sf.write(f.name, final_wave, final_sample_rate)
# Remove silence
if remove_silence:
remove_silence_for_generated_wav(f.name)
print(f.name)


def main():
main_process(ref_audio, ref_text, gen_text, ema_model, mel_spec_type, remove_silence, speed)
def main_process(ref_audio, ref_text, text_gen, model_obj, mel_spec_type, remove_silence, speed, cross_fade_duration):
main_voice = {"ref_audio": ref_audio, "ref_text": ref_text}
if "voices" not in config:
voices = {"main": main_voice}
else:
voices = config["voices"]
voices["main"] = main_voice
for voice in voices:
voices[voice]["ref_audio"], voices[voice]["ref_text"] = preprocess_ref_audio_text(
voices[voice]["ref_audio"], voices[voice]["ref_text"]
)
print("Voice:", voice)
print("Ref_audio:", voices[voice]["ref_audio"])
print("Ref_text:", voices[voice]["ref_text"])

generated_audio_segments = []
reg1 = r"(?=$\w+$)"
chunks = re.split(reg1, text_gen)
reg2 = r"$(\w+)$"
for text in chunks:
if not text.strip():
continue
match = re.match(reg2, text)
if match:
voice = match[1]
else:
print("No voice tag found, using main.")
voice = "main"
if voice not in voices:
print(f"Voice {voice} not found, using main.")
voice = "main"
text = re.sub(reg2, "", text)
gen_text = text.strip()
ref_audio = voices[voice]["ref_audio"]
ref_text = voices[voice]["ref_text"]
print(f"Voice: {voice}")
audio, final_sample_rate, spectragram = infer_process(
ref_audio,
ref_text,
gen_text,
model_obj,
vocoder,
mel_spec_type=mel_spec_type,
speed=speed,
cross_fade_duration=cross_fade_duration
)
generated_audio_segments.append(audio)

if generated_audio_segments:
final_wave = np.concatenate(generated_audio_segments)

if not os.path.exists(output_dir):
os.makedirs(output_dir)

with open(wave_path, "wb") as f:
sf.write(f.name, final_wave, final_sample_rate)
# Remove silence
if remove_silence:
remove_silence_for_generated_wav(f.name)
print(f.name)


def main():
main_process(ref_audio, ref_text, gen_text, ema_model, mel_spec_type, remove_silence, speed, cross_fade_duration)


if __name__ == "__main__":
Expand Down